Architectural computational optimisation in designing acoustics and seating arrangements
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Authors
Li, Yinsu
Popov, Nikolay
Popov, Nikolay
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Date
2024-12-29
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Type
Journal Article
Ngā Upoko Tukutuku (Māori subject headings)
Keyword
performing arts spaces
theatre building design
acoustic architecture
rapid prototyping
digital technologies (DT)
architectural design
theatre building design
acoustic architecture
rapid prototyping
digital technologies (DT)
architectural design
ANZSRC Field of Research Code (2020)
Citation
Li, Y. & Popov, N. Architectural computational optimisation in designing acoustics and seating arrangements. Asylum 1 (2024): 211–220. https://doi.org/10.34074/aslm.2024103
Abstract
In architectural practice, it is challenging for designers to predict future spatial performance based on limited information in the early stages of design. To address this design problem, architectural design optimisation can assist the designer by projecting building performance utilising single or multiple criteria over different architectural geometric analyses in the design process.
The primary purpose of this paper is to describe how to design a computational optimisation program that can automatically generate concept design solutions, and determine its impact on the design outcome. In order to investigate the application of computational optimisation in architecture, this study involved analysis of a small scale community performance facility as the proposed building type in the design exploration. Through this study, a deeper understanding of optimisation processes is intended to contribute to advancing architectural practice through computational generative design.
In the computational generative design process, the designer must abstract design factors to become principle elements in calculations. This paper focuses on how to use algorithmic thinking to formulate design principles, in which the computational design’s benefits and limitations are also discussed. As many optimisation algorithms have been used in architectural design, this paper briefly discusses how to select appropriate algorithms. In computational optimisation, it is important to determine numeric input variables and the objectives of the output, so we review the requirements of the performance-space design to study the feasibility of a range of computational applications. This paper reflects on three experimental design-optimisation programs and studies their computational process through research and evaluation. This study recognises that, while design optimisation generates solutions based on geometric variables and optimisation goals, the outcome it suggests ought not be fundamentally different from that required in the initial design brief.
Publisher
Unitec ePress|Te Pūkenga
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DOI
https://doi.org/10.34074/aslm.2024103
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CC BY-NC-SA Attribution-NonCommercial 4.0 International